WaifuGemma4 26B A4b V1 — Hardware Requirements & GPU Compatibility
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WaifuGemma4 26B A4b V1 is a 25.8B-parameter open language model from hiwaifu-research in the Gemma 4 family. It supports a context window of up to 262,144 tokens. At BF16 it needs about 52.26 GB of VRAM — see which GPUs and Macs can run it below.
1.0K downloads
15 likesSpecifications
- Publisher
- hiwaifu-research
- Family
- Gemma 4
- Parameters
- 25.8B
- Architecture
- Gemma4ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-09-18
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does WaifuGemma4 26B A4b V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 52.3 GB | 96.2 GB | 51.61 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run WaifuGemma4 26B A4b V1?
BF16 · 52.3 GBWaifuGemma4 26B A4b V1 (BF16) requires 52.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 68+ GB is recommended. Using the full 262K context window can add up to 43.9 GB, bringing total usage to 96.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run WaifuGemma4 26B A4b V1?
BF16 · 52.3 GB22 devices with unified memory can run WaifuGemma4 26B A4b V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Related Models
Frequently Asked Questions
- How much VRAM does WaifuGemma4 26B A4b V1 need?
WaifuGemma4 26B A4b V1 requires 52.3 GB of VRAM at BF16. Full 262K context adds up to 43.9 GB (96.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 25.8B × 16 bits ÷ 8 = 51.6 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 44.6 GB (at full 262K context)
VRAM usage by quantization
BF1652.3 GBBF16 + full context96.2 GB- Can NVIDIA GeForce RTX 5090 run WaifuGemma4 26B A4b V1?
No — WaifuGemma4 26B A4b V1 requires at least 52.3 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run WaifuGemma4 26B A4b V1 on a Mac?
WaifuGemma4 26B A4b V1 requires at least 52.3 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run WaifuGemma4 26B A4b V1 locally?
Yes — WaifuGemma4 26B A4b V1 can run locally on consumer hardware. At BF16 quantization it needs 52.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is WaifuGemma4 26B A4b V1?
At BF16, WaifuGemma4 26B A4b V1 can reach ~130 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 52.3 × 0.65 = ~312 tok/s
Estimated speed at BF16 (52.3 GB)
~312 tok/s~312 tok/s~239 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of WaifuGemma4 26B A4b V1?
At BF16, the download is about 51.61 GB.
- Which GPUs can run WaifuGemma4 26B A4b V1?
No single consumer GPU has enough VRAM to run WaifuGemma4 26B A4b V1 at BF16 (52.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run WaifuGemma4 26B A4b V1?
23 devices with unified memory can run WaifuGemma4 26B A4b V1 at BF16 (52.3 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.